In this role, you design, build, and operate AI-native enterprise applications that combine cloud-native software engineering with production-grade machine learning and agentic AI capabilities, embedded directly within customer environments and fast-moving delivery teams. You translate ambiguous business and operational requirements into secure, scalable, and reliable solutions—owning technical delivery from discovery and prototyping through deployment, stabilization, and successful handover to platform or operations teams.
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Responsibilities
- Design, develop, and operate production-grade, cloud-native enterprise applications integrating AI capabilities such as large language models, retrieval-augmented generation (RAG), and agent-based workflows.
- Embed directly into customer projects and fast-moving cross-functional teams to rapidly understand business processes, technical landscapes, and operational challenges.
- Translate business and product requirements into robust application architectures, balancing speed, quality, security, and long-term maintainability.
- Rapidly prototype, iterate, and productionize solutions in customer environments, adapting reference architectures and reusable assets to real-world enterprise constraints.
- Own application delivery end-to-end—from problem framing and prototyping through deployment, observability, and production operations.
- Apply AI-assisted engineering practices, evaluation frameworks, and architectural guardrails to ensure compliant, trustworthy, and high-quality solutions.
- Ensure delivery milestones, quality standards, and technical objectives are met, proactively managing risks and technical escalations within scope.
- Act as a key technical interface to customers and internal stakeholders, clearly communicating solution approaches, trade-offs, and progress.
- Contribute to engineering standards, best practices, and reusable components to improve efficiency and consistency across solutions.
Requirements
- Extensive hands-on experience in software and application engineering for cloud-native, enterprise, and SaaS environments, with strong knowledge of architectural principles such as scalability, security, and reliability.
- Proven ability to design and deliver AI-native applications, utilizing large language models, RAG architectures, vector databases, and agentic systems to innovate enterprise workflows.
- Strong proficiency in widely used AI/ML Python libraries and frameworks, with exposure to data pipelines and MLOps practices.
- Skilled in integrating Agentic AI into complex business processes, ensuring responsible and effective use of AI agents within enterprise operations.
- Strong problem-solving skills, critical thinking, and exposure to design thinking practices; proven ability to mentor teams and establish development guardrails and best practices.
- Proven ability to mentor and inspire teams, establish best development guardrails and practices, and drive engineering culture across delivery teams.
- Strong collaboration and communication skills to work effectively with cross-functional teams and customer stakeholders on complex technical topics.
- Learning mindset, technical leadership, and accountability in high-impact, ambiguous environments; you proactively leverage AI in everyday workflows to ensure high-quality outputs.
Work Conditions
- Expected Travel: 0 - 10%
- Career Status: Professional
- Employment Type: Regular Full Time
- Additional Locations: #LI-Hybrid
Location
Riyadh, SA, 11435
